{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "36ba0bed",
   "metadata": {},
   "source": [
    "### 等宽分箱操作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8fd79308",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore') # 忽略警告"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "33311675",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>男1000米跑</th>\n",
       "      <th>男1000米跑分数</th>\n",
       "      <th>男50米跑</th>\n",
       "      <th>男50米跑分数</th>\n",
       "      <th>男跳远</th>\n",
       "      <th>男跳远分数</th>\n",
       "      <th>男体前屈</th>\n",
       "      <th>男体前屈分数</th>\n",
       "      <th>男引体</th>\n",
       "      <th>男引体分数</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th>男肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.13</td>\n",
       "      <td>72</td>\n",
       "      <td>8.88</td>\n",
       "      <td>66</td>\n",
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       "      <td>2785</td>\n",
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       "      <td>72.599998</td>\n",
       "      <td>25.120001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.16</td>\n",
       "      <td>70</td>\n",
       "      <td>7.70</td>\n",
       "      <td>78</td>\n",
       "      <td>225</td>\n",
       "      <td>74</td>\n",
       "      <td>11</td>\n",
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       "      <td>7</td>\n",
       "      <td>60</td>\n",
       "      <td>3133</td>\n",
       "      <td>68</td>\n",
       "      <td>174</td>\n",
       "      <td>52.700001</td>\n",
       "      <td>17.410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.09</td>\n",
       "      <td>74</td>\n",
       "      <td>8.45</td>\n",
       "      <td>70</td>\n",
       "      <td>218</td>\n",
       "      <td>70</td>\n",
       "      <td>14</td>\n",
       "      <td>78</td>\n",
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       "      <td>0</td>\n",
       "      <td>3901</td>\n",
       "      <td>80</td>\n",
       "      <td>169</td>\n",
       "      <td>46.500000</td>\n",
       "      <td>16.280001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>4.21</td>\n",
       "      <td>68</td>\n",
       "      <td>8.05</td>\n",
       "      <td>74</td>\n",
       "      <td>206</td>\n",
       "      <td>64</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4946</td>\n",
       "      <td>100</td>\n",
       "      <td>183</td>\n",
       "      <td>79.699997</td>\n",
       "      <td>23.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>男</td>\n",
       "      <td>3.44</td>\n",
       "      <td>85</td>\n",
       "      <td>7.52</td>\n",
       "      <td>78</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>68</td>\n",
       "      <td>3538</td>\n",
       "      <td>74</td>\n",
       "      <td>171</td>\n",
       "      <td>54.700001</td>\n",
       "      <td>18.709999</td>\n",
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       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>4.23</td>\n",
       "      <td>68</td>\n",
       "      <td>8.27</td>\n",
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       "      <td>208</td>\n",
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       "      <td>5.19</td>\n",
       "      <td>40</td>\n",
       "      <td>9.55</td>\n",
       "      <td>50</td>\n",
       "      <td>210</td>\n",
       "      <td>66</td>\n",
       "      <td>15</td>\n",
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       "      <td>6</td>\n",
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       "      <td>177</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>24.260000</td>\n",
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       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>3.25</td>\n",
       "      <td>100</td>\n",
       "      <td>7.50</td>\n",
       "      <td>80</td>\n",
       "      <td>252</td>\n",
       "      <td>90</td>\n",
       "      <td>13</td>\n",
       "      <td>76</td>\n",
       "      <td>13</td>\n",
       "      <td>85</td>\n",
       "      <td>5755</td>\n",
       "      <td>100</td>\n",
       "      <td>181</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>19.840000</td>\n",
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       "    <tr>\n",
       "      <th>475</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>4.39</td>\n",
       "      <td>62</td>\n",
       "      <td>7.81</td>\n",
       "      <td>76</td>\n",
       "      <td>208</td>\n",
       "      <td>66</td>\n",
       "      <td>14</td>\n",
       "      <td>78</td>\n",
       "      <td>11</td>\n",
       "      <td>76</td>\n",
       "      <td>5688</td>\n",
       "      <td>100</td>\n",
       "      <td>172</td>\n",
       "      <td>51.700001</td>\n",
       "      <td>17.480000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>476</th>\n",
       "      <td>17</td>\n",
       "      <td>男</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>477 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     班级 性别  男1000米跑  男1000米跑分数  男50米跑  男50米跑分数  男跳远  男跳远分数  男体前屈  男体前屈分数  男引体  \\\n",
       "0     1  男     4.13         72   8.88       66  195     60    12      74    1   \n",
       "1     1  男     4.16         70   7.70       78  225     74    11      74    7   \n",
       "2     1  男     4.09         74   8.45       70  218     70    14      78    1   \n",
       "3     1  男     4.21         68   8.05       74  206     64    13      76    1   \n",
       "4     1  男     3.44         85   7.52       78  210     66    13      76    9   \n",
       "..   .. ..      ...        ...    ...      ...  ...    ...   ...     ...  ...   \n",
       "472  17  男     4.23         68   8.27       72  208     66    10      72    0   \n",
       "473  17  男     5.19         40   9.55       50  210     66    15      80    6   \n",
       "474  17  男     3.25        100   7.50       80  252     90    13      76   13   \n",
       "475  17  男     4.39         62   7.81       76  208     66    14      78   11   \n",
       "476  17  男     0.00          0   0.00        0    0      0     0       0    0   \n",
       "\n",
       "     男引体分数  男肺活量  男肺活量分数   身高         体重        BMI  \n",
       "0        0  2785      62  170  72.599998  25.120001  \n",
       "1       60  3133      68  174  52.700001  17.410000  \n",
       "2        0  3901      80  169  46.500000  16.280001  \n",
       "3        0  4946     100  183  79.699997  23.799999  \n",
       "4       68  3538      74  171  54.700001  18.709999  \n",
       "..     ...   ...     ...  ...        ...        ...  \n",
       "472      0  4647     100  176  69.500000  22.440001  \n",
       "473     50  7042     100  177  76.000000  24.260000  \n",
       "474     85  5755     100  181  65.000000  19.840000  \n",
       "475     76  5688     100  172  51.700001  17.480000  \n",
       "476      0     0       0    0   0.000000   0.000000  \n",
       "\n",
       "[477 rows x 17 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "male = pd.read_excel('./体测分数_男生.xls')     #加载男生体测分数\n",
    "male"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "294ac0df",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
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       " 'DejaVu Sans Mono',\n",
       " 'Garamond',\n",
       " 'Lucida Sans Typewriter',\n",
       " 'Blackadder ITC',\n",
       " 'Microsoft JhengHei',\n",
       " 'Microsoft New Tai Lue',\n",
       " 'Gill Sans MT',\n",
       " 'Lucida Bright',\n",
       " 'FZYaoTi',\n",
       " 'STXinwei',\n",
       " 'Kunstler Script',\n",
       " 'Segoe UI Emoji',\n",
       " 'Franklin Gothic Book',\n",
       " 'Agency FB',\n",
       " 'Gill Sans Ultra Bold',\n",
       " 'Roboto Condensed',\n",
       " 'Arial',\n",
       " 'Microsoft YaHei',\n",
       " 'Sitka Small',\n",
       " 'Candara',\n",
       " 'Consolas',\n",
       " 'Corsiva',\n",
       " 'Rockwell',\n",
       " 'Segoe UI',\n",
       " 'Arial',\n",
       " 'Playbill',\n",
       " 'Cambria',\n",
       " 'Microsoft YaHei',\n",
       " 'Bookman Old Style',\n",
       " 'Gill Sans MT',\n",
       " 'Candara',\n",
       " 'Candara',\n",
       " 'Corsiva',\n",
       " 'Arial Narrow MT Pro',\n",
       " 'Gloucester MT Extra Condensed',\n",
       " 'Book Antiqua',\n",
       " 'Maiandra GD',\n",
       " 'Lucida Fax',\n",
       " 'Bookman Old Style',\n",
       " 'Corbel',\n",
       " 'Microsoft Yi Baiti',\n",
       " 'Times New Roman',\n",
       " 'Garamond',\n",
       " 'Goudy Old Style',\n",
       " 'Open Sans',\n",
       " 'Segoe UI',\n",
       " 'KaiTi',\n",
       " 'SimSun',\n",
       " 'Leelawadee',\n",
       " 'Leelawadee',\n",
       " 'Times New Roman MT',\n",
       " 'STHupo',\n",
       " 'Bodoni MT',\n",
       " 'Candara',\n",
       " 'Roboto',\n",
       " 'Book Antiqua',\n",
       " 'Arial',\n",
       " 'Calibri',\n",
       " 'Copperplate Gothic Light',\n",
       " 'Batang',\n",
       " 'Segoe UI',\n",
       " 'Bodoni MT',\n",
       " 'STSong',\n",
       " 'Rockwell Extra Bold',\n",
       " 'Poiret One',\n",
       " 'Courier New',\n",
       " 'Lucida Sans',\n",
       " 'Segoe UI',\n",
       " 'MS Gothic',\n",
       " 'Microsoft JhengHei',\n",
       " 'Raleway',\n",
       " 'Yu Gothic',\n",
       " 'Tahoma',\n",
       " 'Segoe UI',\n",
       " 'Segoe UI',\n",
       " 'Berlin Sans FB',\n",
       " 'Britannic Bold',\n",
       " 'Bradley Hand ITC',\n",
       " 'Palatino Linotype',\n",
       " 'Corbel',\n",
       " 'Verdana',\n",
       " 'Bell MT',\n",
       " 'Arial Narrow MT Std',\n",
       " 'Segoe UI',\n",
       " 'Microsoft Uighur',\n",
       " 'Bookman Old Style',\n",
       " 'STLiti',\n",
       " 'Wingdings 2',\n",
       " 'Papyrus',\n",
       " 'Bookshelf Symbol 1',\n",
       " 'Century Schoolbook',\n",
       " 'Microsoft Uighur',\n",
       " 'Franklin Gothic Medium Cond',\n",
       " 'SimSun-ExtB',\n",
       " 'Franklin Gothic Demi',\n",
       " 'Haettenschweiler',\n",
       " 'Corbel',\n",
       " 'Tw Cen MT Condensed',\n",
       " 'Century Gothic',\n",
       " 'Franklin Gothic Demi',\n",
       " 'FZCuHeiSongS-B-GB',\n",
       " 'Cambria',\n",
       " 'Century Schoolbook',\n",
       " 'Lucida Bright',\n",
       " 'Eras Demi ITC',\n",
       " 'DejaVu Sans Mono',\n",
       " 'Sitka Small',\n",
       " 'Calibri',\n",
       " 'Wingdings 3',\n",
       " 'Garamond',\n",
       " 'Yu Gothic',\n",
       " 'French Script MT',\n",
       " 'Franklin Gothic Medium',\n",
       " 'Microsoft Himalaya',\n",
       " 'Brush Script MT',\n",
       " 'Times New Roman',\n",
       " 'High Tower Text',\n",
       " 'Sylfaen',\n",
       " 'Leelawadee UI',\n",
       " 'Calisto MT',\n",
       " 'Arial Unicode MS',\n",
       " 'Century Schoolbook',\n",
       " 'Chiller',\n",
       " 'Perpetua',\n",
       " 'Comic Sans MS',\n",
       " 'Franklin Gothic Medium',\n",
       " 'Monotype Corsiva',\n",
       " 'Segoe UI',\n",
       " 'Nirmala UI',\n",
       " 'FangSong',\n",
       " 'Book Antiqua',\n",
       " 'Open Sans',\n",
       " 'Arial Black',\n",
       " 'Verdana',\n",
       " 'Bodoni MT',\n",
       " 'Bodoni MT',\n",
       " 'Lucida Bright',\n",
       " 'Showcard Gothic',\n",
       " 'Stencil',\n",
       " 'Corbel',\n",
       " 'Lucida Fax',\n",
       " 'Bookshelf Symbol 7',\n",
       " 'MS Reference Sans Serif',\n",
       " 'Leelawadee UI',\n",
       " 'Onyx',\n",
       " 'Roboto',\n",
       " 'Modern No. 20',\n",
       " 'Malgun Gothic',\n",
       " 'Vladimir Script',\n",
       " 'Bookshelf Symbol 2',\n",
       " 'Comic Sans MS',\n",
       " 'Elephant',\n",
       " 'Arial Rounded MT Bold',\n",
       " 'STCaiyun',\n",
       " 'Book Antiqua',\n",
       " 'Ebrima',\n",
       " 'Candara',\n",
       " 'Garamond',\n",
       " 'Segoe Print',\n",
       " 'Tw Cen MT',\n",
       " 'Calisto MT',\n",
       " 'DejaVu Sans Mono',\n",
       " 'Tw Cen MT',\n",
       " 'Magneto',\n",
       " 'STFangsong',\n",
       " 'Lucida Sans Unicode',\n",
       " 'Consolas',\n",
       " 'Georgia',\n",
       " 'Kristen ITC',\n",
       " 'Georgia',\n",
       " 'Open Sans',\n",
       " 'Segoe UI Symbol',\n",
       " 'Book Antiqua',\n",
       " 'Droid Serif',\n",
       " 'icomoon',\n",
       " 'Gadugi',\n",
       " 'Calibri',\n",
       " 'Wingdings 3',\n",
       " 'MS Outlook',\n",
       " 'Myanmar Text',\n",
       " 'Microsoft PhagsPa',\n",
       " 'Franklin Gothic Demi Cond',\n",
       " 'Monotype Sorts',\n",
       " 'Nirmala UI',\n",
       " 'Informal Roman',\n",
       " 'Bauhaus 93',\n",
       " 'Berlin Sans FB Demi',\n",
       " 'Symbol',\n",
       " 'Segoe UI',\n",
       " 'Castellar',\n",
       " 'Book Antiqua',\n",
       " 'Open Sans',\n",
       " 'Bodoni MT',\n",
       " 'DejaVu Sans Mono',\n",
       " 'Juice ITC',\n",
       " 'Open Sans',\n",
       " 'STXingkai',\n",
       " 'Palatino Linotype',\n",
       " 'Trebuchet MS',\n",
       " 'Bookman Old Style',\n",
       " 'Tw Cen MT',\n",
       " 'Goudy Old Style',\n",
       " 'Tahoma',\n",
       " 'Bernard MT Condensed',\n",
       " 'Baskerville Old Face',\n",
       " 'Consolas',\n",
       " 'Arial WGL',\n",
       " 'Roboto',\n",
       " 'Felix Titling',\n",
       " 'SimHei',\n",
       " 'Yu Gothic',\n",
       " 'Sitka Small',\n",
       " 'Gigi',\n",
       " 'Lucida Bright',\n",
       " 'Verdana',\n",
       " 'Calibri',\n",
       " 'Droid Serif',\n",
       " 'Courier New',\n",
       " 'Marlett',\n",
       " 'Open Sans',\n",
       " 'Arial',\n",
       " 'Times New Roman']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from matplotlib.font_manager import FontManager        #电脑上的所有字体显示中文字体\n",
    "fm = FontManager()   \n",
    "[font.name for font in fm.ttflist]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41403484",
   "metadata": {},
   "source": [
    "#### 男1000米跑饼图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9eeda60b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x1 = pd.cut(male[\"男1000米跑\"],                     #对男10000米跑等宽分箱操作       \n",
    "       bins = 3,\n",
    "       labels = [\"慢速\",\"中速\",\"快速\"],\n",
    "       right = True).value_counts()\n",
    "percent1 = x1/x1.sum()\n",
    "percent1\n",
    "plt.figure(figsize=(6,6))    #图形尺寸\n",
    "_=plt.pie(percent1,\n",
    "          labels= [\"慢速\",\"中速\",\"快速\"],\n",
    "          textprops={\"family\":'KaiTi','fontsize':20},\n",
    "          autopct='%0.2f%%', #显示百分比\n",
    "          explode = (0.1,0,0),   #突出某一部分\n",
    "          shadow=True) \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a744a4d",
   "metadata": {},
   "source": [
    "#### 男引体饼图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4242d189",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x2 = pd.cut(male[\"男引体\"],                     #对男引体等宽分箱操作       \n",
    "       bins = 3,\n",
    "       labels = [\"慢速\",\"中速\",\"快速\"],\n",
    "       right = True).value_counts()\n",
    "percent2 = x2/x2.sum()\n",
    "percent2\n",
    "\n",
    "plt.figure(figsize=(6,6))    #图形尺寸\n",
    "_=plt.pie(percent2,\n",
    "          labels=[\"慢速\",\"中速\",\"快速\"],\n",
    "          textprops={\"family\":'KaiTi','fontsize':20},\n",
    "          autopct='%0.2f%%',   #显示百分比\n",
    "          explode = (0.1,0,0),  #突出某一部分\n",
    "          shadow=True) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c087d174",
   "metadata": {},
   "source": [
    "### 直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ae9829a9",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>班级</th>\n",
       "      <th>性别</th>\n",
       "      <th>女800米跑</th>\n",
       "      <th>女800米跑分数</th>\n",
       "      <th>女50米跑</th>\n",
       "      <th>女50米跑分数</th>\n",
       "      <th>女跳远</th>\n",
       "      <th>女跳远分数</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>女体前屈分数</th>\n",
       "      <th>女仰卧</th>\n",
       "      <th>女仰卧分数</th>\n",
       "      <th>女肺活量</th>\n",
       "      <th>女肺活量分数</th>\n",
       "      <th>身高</th>\n",
       "      <th>体重</th>\n",
       "      <th>BMI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.22</td>\n",
       "      <td>100</td>\n",
       "      <td>9.32</td>\n",
       "      <td>72</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>16</td>\n",
       "      <td>76</td>\n",
       "      <td>48</td>\n",
       "      <td>85</td>\n",
       "      <td>3775</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>51.299999</td>\n",
       "      <td>19.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>4.59</td>\n",
       "      <td>40</td>\n",
       "      <td>11.44</td>\n",
       "      <td>10</td>\n",
       "      <td>148</td>\n",
       "      <td>60</td>\n",
       "      <td>9</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>3683</td>\n",
       "      <td>100</td>\n",
       "      <td>163.0</td>\n",
       "      <td>66.599998</td>\n",
       "      <td>25.070000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.46</td>\n",
       "      <td>80</td>\n",
       "      <td>13.40</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>7</td>\n",
       "      <td>64</td>\n",
       "      <td>40</td>\n",
       "      <td>76</td>\n",
       "      <td>3331</td>\n",
       "      <td>100</td>\n",
       "      <td>157.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>24.340000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.39</td>\n",
       "      <td>85</td>\n",
       "      <td>9.52</td>\n",
       "      <td>70</td>\n",
       "      <td>172</td>\n",
       "      <td>76</td>\n",
       "      <td>21</td>\n",
       "      <td>90</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3701</td>\n",
       "      <td>100</td>\n",
       "      <td>160.0</td>\n",
       "      <td>50.700001</td>\n",
       "      <td>19.799999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>女</td>\n",
       "      <td>3.43</td>\n",
       "      <td>80</td>\n",
       "      <td>9.79</td>\n",
       "      <td>68</td>\n",
       "      <td>145</td>\n",
       "      <td>50</td>\n",
       "      <td>8</td>\n",
       "      <td>64</td>\n",
       "      <td>34</td>\n",
       "      <td>70</td>\n",
       "      <td>3592</td>\n",
       "      <td>100</td>\n",
       "      <td>167.0</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>22.910000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>588</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>3.51</td>\n",
       "      <td>78</td>\n",
       "      <td>9.60</td>\n",
       "      <td>68</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>24</td>\n",
       "      <td>95</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>2255</td>\n",
       "      <td>70</td>\n",
       "      <td>158.0</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>19.629999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>589</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.00</td>\n",
       "      <td>76</td>\n",
       "      <td>10.18</td>\n",
       "      <td>64</td>\n",
       "      <td>150</td>\n",
       "      <td>60</td>\n",
       "      <td>13</td>\n",
       "      <td>72</td>\n",
       "      <td>36</td>\n",
       "      <td>72</td>\n",
       "      <td>2937</td>\n",
       "      <td>85</td>\n",
       "      <td>161.0</td>\n",
       "      <td>55.700001</td>\n",
       "      <td>21.490000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>590</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>3.45</td>\n",
       "      <td>80</td>\n",
       "      <td>10.18</td>\n",
       "      <td>64</td>\n",
       "      <td>152</td>\n",
       "      <td>62</td>\n",
       "      <td>15</td>\n",
       "      <td>76</td>\n",
       "      <td>35</td>\n",
       "      <td>72</td>\n",
       "      <td>2592</td>\n",
       "      <td>76</td>\n",
       "      <td>165.0</td>\n",
       "      <td>48.599998</td>\n",
       "      <td>17.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.01</td>\n",
       "      <td>74</td>\n",
       "      <td>9.67</td>\n",
       "      <td>68</td>\n",
       "      <td>165</td>\n",
       "      <td>70</td>\n",
       "      <td>10</td>\n",
       "      <td>68</td>\n",
       "      <td>41</td>\n",
       "      <td>78</td>\n",
       "      <td>1829</td>\n",
       "      <td>60</td>\n",
       "      <td>154.0</td>\n",
       "      <td>43.599998</td>\n",
       "      <td>18.379999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>592</th>\n",
       "      <td>17</td>\n",
       "      <td>女</td>\n",
       "      <td>4.48</td>\n",
       "      <td>50</td>\n",
       "      <td>9.09</td>\n",
       "      <td>74</td>\n",
       "      <td>180</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>68</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>2962</td>\n",
       "      <td>85</td>\n",
       "      <td>162.0</td>\n",
       "      <td>55.299999</td>\n",
       "      <td>21.070000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>593 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     班级 性别  女800米跑  女800米跑分数  女50米跑  女50米跑分数  女跳远  女跳远分数  女体前屈  女体前屈分数  女仰卧  \\\n",
       "0     1  女    3.22       100   9.32       72  185     85    16      76   48   \n",
       "1     1  女    4.59        40  11.44       10  148     60     9      66   29   \n",
       "2     1  女    3.46        80  13.40        0  150     60     7      64   40   \n",
       "3     1  女    3.39        85   9.52       70  172     76    21      90   46   \n",
       "4     1  女    3.43        80   9.79       68  145     50     8      64   34   \n",
       "..   .. ..     ...       ...    ...      ...  ...    ...   ...     ...  ...   \n",
       "588  17  女    3.51        78   9.60       68  150     60    24      95   41   \n",
       "589  17  女    4.00        76  10.18       64  150     60    13      72   36   \n",
       "590  17  女    3.45        80  10.18       64  152     62    15      76   35   \n",
       "591  17  女    4.01        74   9.67       68  165     70    10      68   41   \n",
       "592  17  女    4.48        50   9.09       74  180     80    10      68   46   \n",
       "\n",
       "     女仰卧分数  女肺活量  女肺活量分数     身高         体重        BMI  \n",
       "0       85  3775     100  163.0  51.299999  19.309999  \n",
       "1       66  3683     100  163.0  66.599998  25.070000  \n",
       "2       76  3331     100  157.0  60.000000  24.340000  \n",
       "3       85  3701     100  160.0  50.700001  19.799999  \n",
       "4       70  3592     100  167.0  63.900002  22.910000  \n",
       "..     ...   ...     ...    ...        ...        ...  \n",
       "588     78  2255      70  158.0  49.000000  19.629999  \n",
       "589     72  2937      85  161.0  55.700001  21.490000  \n",
       "590     72  2592      76  165.0  48.599998  17.850000  \n",
       "591     78  1829      60  154.0  43.599998  18.379999  \n",
       "592     85  2962      85  162.0  55.299999  21.070000  \n",
       "\n",
       "[593 rows x 17 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "female = pd.read_excel('./体测分数_女生.xls')      #加载女生体测分数\n",
    "female"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1a25608",
   "metadata": {},
   "source": [
    "#### 女800米跑直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7e0c031b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y1=female[\"女800米跑分数\"]\n",
    "y1\n",
    "count,bins,fig=plt.hist(y1,4,color='orange')    #fig为图形"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b189ed3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 37.,  15., 157., 384.])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([  0.,  25.,  50.,  75., 100.])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(count,bins)         #count统计范围，bins范围"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d4c101d",
   "metadata": {},
   "source": [
    "#### 女跳远直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9764a47d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y2=female['女跳远分数']\n",
    "y2\n",
    "count,bins,fig=plt.hist(y2,4,color='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5df5d967",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 19.,  10., 416., 148.])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([  0.,  25.,  50.,  75., 100.])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(count,bins) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a14506ad",
   "metadata": {},
   "source": [
    "### 嵌套饼图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "92e02537",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "正常     0.755365\n",
       "超重     0.130901\n",
       "肥胖     0.081545\n",
       "低体重    0.032189\n",
       "Name: BMI, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x3=pd.cut(male[\"BMI\"],        \n",
    "      bins = [0,16.5,23.2,26.4,40],\n",
    "       labels=[\"低体重\",\"正常\",\"超重\",\"肥胖\"]).value_counts()\n",
    "x3                                                \n",
    "percent3= x3/x3.sum()\n",
    "percent3                         #男生体重指数各区间求百分比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "5acf040b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "正常     0.747440\n",
       "超重     0.145051\n",
       "肥胖     0.088737\n",
       "低体重    0.018771\n",
       "Name: BMI, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y3=pd.cut(female[\"BMI\"],\n",
    "      bins = [0,16.5,22.7,25.2,40],\n",
    "       labels=[\"低体重\",\"正常\",\"超重\",\"肥胖\"]).value_counts()\n",
    "y3\n",
    "percent4= y3/y3.sum()\n",
    "percent4                      #女生体重指数各区间求百分比      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e81f6663",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2145f520488>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "percent3  #外圆\n",
    "percent4  #内圆\n",
    "\n",
    "plt.figure(figsize=(9,9))\n",
    "plt.pie(percent3,radius=1,\n",
    "       autopct='%0.2f%%',\n",
    "       pctdistance=0.85,\n",
    "       labels=[\"低体重\",\"正常\",\"超重\",\"肥胖\"],\n",
    "       wedgeprops={'linewidth':5,  #间隔宽度\n",
    "                 'width':0.3,      #饼图的宽度\n",
    "                   \"edgecolor\":\"white\" },#间隔的颜色\n",
    "       textprops={\"family\":'KaiTi','fontsize':20})\n",
    "\n",
    "\n",
    "_=plt.pie(percent4,radius=0.7,\n",
    "       autopct='%0.2f%%',\n",
    "       pctdistance=0.55,\n",
    "       wedgeprops={'linewidth':5,\n",
    "                 'width':0.7,\n",
    "                   'edgecolor':'white' })\n",
    "      \n",
    "plt.rcParams['font.family'] = 'KaiTi'\n",
    "plt.rcParams['font.size'] = 11\n",
    "    \n",
    "plt.legend([\"低体重\",\"正常\",\"超重\",\"肥胖\"],title='男女生体重指数分布',prop ='KaiTi')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6fccb7a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
